🔗 Who cites «Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?»

32 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · ← back to «Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?»

1. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
2. Token-Budget-Aware LLM ReasoningarXiv:2412.18547Tingxu Han, Zhenting Wang, Chunrong Fang, et al.2024 · 136 citations
3. Disentangling Memory and Reasoning Ability in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingyu Jin, Weidi Luo, Sitao Cheng, et al.2025 · 45 citations
4. AGrail: A Lifelong Agent Guardrail with Effective and Adaptive Safety DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Weidi Luo, Shenghong Dai, Xiaogeng Liu, et al.2025 · 20 citations
5. NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-NeuronsAnnual Meeting of the Association for Computational Linguistics (ACL)Haonan Dong, Kehan Jiang, Haoran Ye, et al.2026 · 13 citations
6. Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuchen Fu, Zifeng Cheng, Zhiwei Jiang, et al.2025 · 10 citations
7. Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language ModelsFindings of the Association for Computational LinguisticsHengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.2026 · 9 citations
8. GMSA: Enhancing Context Compression via Group Merging and Layer Semantic AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Jiwei Tang, Zhicheng Zhang, Shunlong Wu, et al.2026 · 8 citations
9. GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model RecommendationFindings of the Association for Computational LinguisticsLin Mu, Guoji Wang, Li Ni, et al.2026
10. How Do LLMs Generate Contrastive Sentiments? A Mechanistic PerspectiveConference of the European Chapter of the Association for Computational Linguistics (EACL)Van Bach Nguyen, Jörg Schlötterer, Christin Seifert2026
11. Learning Uncertainty from Sequential Internal Dispersion in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.2026

21 more papers of our library cite it; they have no page here yet.

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